Replacing 100% of phenol in phenolic adhesive formulations with lignin
Bibliographic record
Abstract
ABSTRACT Lignin, produced as a byproduct of pulp and paper and bioethanol industries, is a polyphenolic compound that has excellent potential to be used as phenol replacement in phenolic adhesive formulation. In this study, the phenol portion of phenol formaldehyde (PF) resin has been replaced by an agricultural‐based lignin, which was produced as a byproduct of a cellulosic bioethanol process through dilute‐acid pretreatment and enzymatic hydrolysis from corn stover. The PF resol resin was formulated using isolated lignin under alkaline condition. Chemical, physical, and thermal properties of the isolated lignin, PF resin and adhesive were measured using advanced analytical techniques such as Fourier transformed infrared spectroscopy (FTIR), size exclusion chromatography (SEC), phosphorous nuclear magnetic resonance spectroscopy (31P NMR), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). The developed 100% lignin‐based adhesive and a commercially formulated phenol resorcinol formaldehyde (PRF, as reference) were used to prepare single‐lap‐joint samples for mechanical testing. The plywood samples were pressed under exactly the same conditions (time, temperature, and pressure) as what recommended for the commercial PRF formulation. According to two‐way ANOVA results, statistically there was no significant difference between the shear strengths of plywood samples made with 100% lignin‐based adhesive and those made with the commercial PRF resin. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 45124.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".